Saturday, 25 November 2017

An illustration of several different ways of using internal and external calipers for measuring in the engineering workshop. From an illustrated handbook on how to use a lathe for a wide range of engineering work. By Ray S. Lindenmeyer, Assistant Professor of Industrial Engineering at Northwestern Technological Institute, Evanston, Illinois. Full handbook is HERE.

Saturday, 18 November 2017

The Astronomicum Caesarium (1540) by Petrus Apianus is a beautiful book of mathematical tables and working paper mathematical devices. It is one of the most beautiful and complex hand printed books ever produced. A full high resolution scan and historical notes are HERE.

Friday, 17 November 2017

"...in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it"

A piece HERE in The Paris Review by the photographer Joel Meyerowitz on the grey-green walls of Cézanne’s studio, the effect this had on how he saw the objects in the studio, and his photographs of items from the studio.

An attempt to understand the magnitude of bias in scientific studies by Daniele Fanelli, Rodrigo Costas, and John P. A. Ioannidis (HERE).

The Abstract reads:

Numerous biases are believed to affect the scientific literature, but their actual prevalence across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, we probed for the most commonly postulated bias-related patterns and risk factors, in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, we consistently observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them. We also found at least partial confirmation of previous evidence suggesting that US studies and early studies might report more extreme effects, although these effects were smaller and more heterogeneously distributed across meta-analyses and disciplines. Authors publishing at high rates and receiving many citations were, overall, not at greater risk of bias. However, effect sizes were likely to be overestimated by early-career researchers, those working in small or long-distance collaborations, and those responsible for scientific misconduct, supporting hypotheses that connect bias to situational factors, lack of mutual control, and individual integrity. Some of these patterns and risk factors might have modestly increased in intensity over time, particularly in the social sciences. Our findings suggest that, besides one being routinely cautious that published small, highly-cited, and earlier studies may yield inflated results, the feasibility and costs of interventions to attenuate biases in the literature might need to be discussed on a discipline-specific and topic-specific basis.

Wednesday, 8 November 2017

A lean, fleet-footed translation that recaptures Homer’s “nimble gallop” and brings an ancient epic to new life.

The first great adventure story in the Western canon, The Odyssey is a poem about violence and the aftermath of war; about wealth, poverty, and power; about marriage and family; about travelers, hospitality, and the yearning for home.

In this fresh, authoritative version—the first English translation of The Odyssey by a woman—this stirring tale of shipwrecks, monsters, and magic comes alive in an entirely new way. Written in iambic pentameter verse and a vivid, contemporary idiom, this engrossing translation matches the number of lines in the Greek original, thus striding at Homer’s sprightly pace and singing with a voice that echoes Homer’s music.

Wilson’s Odyssey captures the beauty and enchantment of this ancient poem as well as the suspense and drama of its narrative. Its characters are unforgettable, from the cunning goddess Athena, whose interventions guide and protect the hero, to the awkward teenage son, Telemachus, who struggles to achieve adulthood and find his father; from the cautious, clever, and miserable Penelope, who somehow keeps clamoring suitors at bay during her husband’s long absence, to the “complicated” hero himself, a man of many disguises, many tricks, and many moods, who emerges in this translation as a more fully rounded human being than ever before.

A fascinating introduction provides an informative overview of the Bronze Age milieu that produced the epic, the major themes of the poem, the controversies about its origins, and the unparalleled scope of its impact and influence. Maps drawn especially for this volume, a pronunciation glossary, and extensive notes and summaries of each book make this an Odyssey that will be treasured by a new generation of scholars, students, and general readers alike.

Not only does leaf shape vary between Passiflora species, but between sequential nodes of the vine. The profound changes in leaf shape within Passiflora vines reflect the temporal development of the shoot apical meristem from which leaves are derived and patterned, a phenomenon known as heteroblasty. We perform a morphometric analysis of more than 3,300 leaves from 40 different Passiflora species using two different methods: homologous landmarks and Elliptical Fourier Descriptors (EFDs). Changes in leaf shape across the vine are first quantified in allometric terms; that is, changes in the relative area of leaf subregions expressed in terms of overall leaf area. Shape is constrained to strict linear relationships as a function of size that vary between species. Statistical analysis of leaf shape, using landmarks and EFDs, reveals that species effects (regardless of node) are the strongest, followed by interaction effects between species and heteroblasty (i.e., species-specific patterns in leaf shape across nodes) and that heteroblasty effects across nodes (regardless of species) are negligible. The ability of different nodes to predictively discriminate species and the variability of landmark and EFD traits at each node is then analyzed. Heteroblastic trajectories, the changes in leaf shape between the first and last measured leaves in a vine, are then compared between species in a multivariate space. Leaf shape diversity among Passiflora species is expressed in a heteroblastic-dependent manner, unique to each species. Leaf shape is constrained by linear, allometric relationships related to leaf size that vary between species. There is a strong species × heteroblasty interaction effect for leaf shape, suggesting that different leaf shapes between species arise through changes in shape across nodes specific to each species. The first leaves in the series are not only more like each other, but are also less variable across species. From this similar, shared leaf shape, subsequent leaves in the heteroblastic series follow divergent morphological trajectories. The disparate leaf shapes characteristic of Passiflora species arise from a shared, juvenile morphology.

Sunday, 5 November 2017

Far too often, in the current headlong rush to apply machine learning and predictive modelling to data, people are wont to forget the Central paradox of Data:It is impossible to assess whether a given piece of data is any good or not, simply by inspection of the data alone.

This paradox is as true for a Gigabyte of electronic data records in a fancy database, as an individual measurement of the weight of a bag of sweets in grams. It is true for the simplest application of the fundamental statistical question: Compared to What?, as well as the most complex multi-layered questioning of a predictive model (weighing a bag of sweets is a comparison: what is it's mass compared to a standardised unit of mass - the gram).

How to proceed?

Here is a superb, modestly written explanation by Daniel Haight of the reality of what is involved in real data analysis.

He describes 7 steps:

Gather data from inside and outside the firewall

Understand (and document) your sources and their limitations

Clean up the duplicates, blanks, and other simple errors

Join all your data into a single table

Create new data by calculating new fields and recategorizing

Visualize the data to remove outliers and illogical results

Share your findings continuously

I recognise these steps, because this is what I learned by a process of tinkering and making mistakes nearly 30 years ago when I was a Data Wrangler; using image analysis kit, cameras and lenses, Lotus 1-2-3 macros, FORTRAN and C programming languages and hand made data visualisations.

Friday, 3 November 2017

HERE is the second in a series of eight pieces in The Paris Review by Jeff Dolven, in which he, "will take apart and put back together one beloved or bedeviling sentence every week". This week it is a sentence from Virginia Woolf’s book The Waves (1931): The trees wave, the clouds pass.

Which is not to say that there is any law against reversing them. “The clouds pass, the trees wave.” This is a different sentence, but not an illegal one, not the way the intransitive “wave the trees” would be. We have come to the limits of what grammar will dictate, and other laws, less scrutable and less fair, take over. In Louis’s sentence there is a bare appeal to grammar-as-nature, compliance with the rules of construction at their minimum. But his sighing comma is not grammatical, really, since it puts two clauses together that could just as well be parsed by two periods, and whatever relation obtains between two sentences is beyond grammar’s reach. Enter logic, rhetoric, poetics. With that comma, Woolf releases the sentence into the hazards of choice, of constructions that might be otherwise. The shimmer of alternatives is a basic property of a literary sentence, and all the pathos, and beauty, of this one—in its poignant minimalism—lies in the possibility that it might have run the other way and the fact that it does not. All our soliloquies share grammar, but from there they must diverge.